目的利用医学图像融合技术为临床提供新的诊断信息。
Objective To provide new diagnose informations for clinician by using image fusion.
本文主要内容是关于多模态医学图像融合的研究和实现。
This paper aims at pilot study on multimodality medical image fusion.
多模态医学图像融合在医学图像的分析和诊断上具有极为重要的应用价值。
Multi-modality medical image fusion plays an important role in medical analysis and diagnosis.
医学图像融合的效果评价方法有很多，如信息熵、互信息、均方值、峰值信噪比和平均梯度等。
There are many kinds of image fusion methods, such as information entropy, mutual information, mean square error, peak signal to noise ratio and mean grads.
医学图像配准是医学图像融合的前提，是目前医学图像处理中的热点，具有重要的临床诊断和治疗价值。
Medical image registration, as the prerequisite for medical image fusion, is a hot field in the medical image processing and commonly used for clinical diagnosis and treatment.
医学图像融合是医学图像后处理的研究热点，它充分利用多模式图像，获得互补信息，使临床的诊断和治疗更加准确完善。
Image fusion is a research focus of medical image processing. Proper registrations were desired in clinical diagnoses and therapy to obtain complementary information from multi modality images.
图像融合是图像分析和处理的基本问题，在医学影像领域有着广泛的应用。
Image fusion is fundamental problem in image analysis and processing, and is used widely in medical imaging.
医学图像的配准和融合是医学图像处理的一个新的领域，其目的是为医生提供更多的诊断信息。
Medical image registration and merging is a new area in medical image processing the purpose is to provide more diagnostic information to the physicians.
图像融合作为信息融合的一个重要领域已广泛应用于遥感、医学、计算机视觉、军事目标探测和识别等多方面。
As a very important field of information fusion, image fusion has been extensively applied in remote sensing, medical science, computer vision, detecting and identification of military target etc.
在此基础上提出了一种混合区域信息和边界信息的方法——基于融合颜色和强度先验信息的几何可变模型的医学图像分割算法。
Then a new method merging area information and edge information, geometric deformable model with color and intensity priors for medical image segmentation, is proposed.
图像融合技术在现代医学中扮演着极其重要的角色，是现代医学图像技术研究的重点。
Image fusion plays an even most significant role in the field of modern medical now, and it is the core of research of image technology.
图像融合是医学图像处理中的关键技术。
Image fusion is a key technology on medical images progressing.
提出一种基于模糊数学的方法来融合多模医学图像。
In this paper, a method based on fuzzy mathematics to fuse multimodality medical images was presented.
近年来，图像融合技术在现代航空航天、自动控制、遥感遥测、医学，特别是军事指挥领域中发挥着越来越重要的作用。
In recent years, the technology of image fusion has played an increasingly important role in modern aerospace, automation, remote control and medicine, particularly in the field of military guidance.
图像融合是医学图像处理中的关键技术。
Image fusion is a key technology in medical images progressing.
目的探索建立三维核医学图像配准和融合进行心肌存活评价的定量分析方法。
Objective To establish a new quantitative analyzing method for myocardial viability evaluation based on the 3-d registration and fusion of the nuclear medicine images.
目前，多传感器图像融合技术在医学、遥感、计算机视觉、气象预报、自动目标检测等领域得到了广泛应用。
Now multi-sensor image fusion is widely applied in some fields, such as medicine, remote sensing, computer vision, weather forecast, automatic object detection, etc.
它不仅可以将同一病人的切片图像进行配准融合以便于医学诊断，而且可以将不同病人之间以及病人与标准图谱之间进行处理。
We can't only do this in different cross-sections of same patient, but also do it between different patients, and images of patient to standard atlas.
图像融合技术在遥感、医学、自然资源勘探、海洋资源管理、地形地貌分析、生物学等领域占有极其重要的地位。
Image fusion technology occupies important places in the fields of remote sensing, medicine, natural resource exploration, Marine resource management, terrain landform analysis and biology.
医学图像配准作为图像融合的先决条件，它的研究是医学图像处理领域的热点。
Medical image registration as a prerequisite for image fusion, its research is a hot in the area of medical image processing.
利用图像融合技术，将不同模态的医学图像有机地结合在一起，可以充分利用各种医学图像的优点，为临床诊断和治疗提供帮助。
Using the technologies of image fusion, we can combine the multimodality medical image information efficiently which is very helpful for clinical diagnoses and treatment.
另外，同机SPECT和CT或符合线路PET和CT的图像融合，为核医学的功能图像提供了解剖学定位。
In addition, the image fusion of SPECT and ct or coincidence PET and ct in one modality provides anatomic localization for the functional image of nuclear medicine.
它利用医学影像作为原始数据，融合图像处理、计算机图形学、科学计算可视化、虚拟现实技术，模拟传统光学内窥镜的一种技术。
It simulates optics endoscopy with medical images. Virtual endoscopy incorporates Computer Graphics, image Processing, Scientific Computing Visualization, and Virtual Reality, etc.
医学图像配准与信息融合是当代信息科学、计算机图像技术与当代医学等多学科交叉的一个研究领域。
Medical image registration and fusion is a crossing research topic of information science, computer image technology and modern medicine.
它利用医学影像作为原始数据，融合图像处理、计算机图形学、科学计算可视化、虚拟现实技术，模拟传统光学内窥镜的一种技术。
It simulates optics endoscopy by use of medical images. Virtual endoscopy incorporates the research about Computer Graphics, image Processing, Scientific Computing Visualization, Virtual Reality, etc.
为了实现多模态医学图像的配准融合，提出一种加快寻优的医学图像互信息配准算法实现CT和MR图像的配准。
A new medical image mutual information registration method, which can speedup the optimized process is proposed for CT and MR medical image auto rigid registration.
这种将不同模式的图像信息整合成一种新模式的图像称为医学图像的融合，而融合的第一步先要配准。
The new image which is integrated from different modes images called the medical image fusion and the first step of fusion is image registration.
对普通图像、航拍图像和医学图像分别进行融合操作，并将融合结果与已知图像的熵和交叉熵作为客观评价指标，与相应小波融合方法进行了比较。
Objective parameters of evaluating the fusion performance are provided via entropy and cross entropy. Comparisons of performance of Brushlet-based and wavelet-based fusion methods are provided.
医学图像配准是医学图像处理中的一个重要研究课题，它是图像融合、图像与标准图谱的匹配、显微图像的重建等研究的基础。
Image registration is an important subject in medical image processing. It is fundamental for image matching with atlas, image fusion and micrograph reconstruction.
医学图像配准是医学图像处理中的一个重要研究课题，它是图像融合、图像与标准图谱的匹配、显微图像的重建等研究的基础。
Image registration is an important subject in medical image processing. It is fundamental for image matching with atlas, image fusion and micrograph reconstruction.
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